feat: enhance AIPlanner payload structure for LM Studio compatibility by including 'input' field and improve response content extraction methods

tests/test_ai_planner_lmstudio_compat.py

@@ -0,0 +1,37 @@
+import unittest
+
+from ai_planner import AIPlanner
+
+
+class TestAIPlannerLMStudioCompat(unittest.TestCase):
+    def test_build_chat_payload_includes_input_for_responses_compat(self):
+        payload = AIPlanner._build_chat_payload("hello")
+
+        self.assertIn("messages", payload)
+        self.assertIn("input", payload)
+        self.assertEqual(payload["input"], "hello")
+        self.assertEqual(payload["messages"][1]["content"], "hello")
+
+    def test_extract_response_content_supports_message_content(self):
+        data = {
+            "message": {
+                "content": (
+                    '{"thinking":"t","current_goal":"g","actions":[],"after_this":"a"}'
+                )
+            }
+        }
+        content = AIPlanner._extract_response_content(data)
+        self.assertIn('"current_goal":"g"', content)
+
+    def test_extract_response_content_supports_output_text(self):
+        data = {
+            "output_text": (
+                '{"thinking":"t","current_goal":"g","actions":[],"after_this":"a"}'
+            )
+        }
+        content = AIPlanner._extract_response_content(data)
+        self.assertIn('"after_this":"a"', content)
+
+
+if __name__ == "__main__":
+    unittest.main()